Science Editing

Original Articles

Factors influencing authors’ intention to continue publishing in data journals: a cross-sectional survey: Seungeun Lee, Jihyun Kim; Sci Ed. 2025;12(2):183-189. Published online August 7, 2025; DOI: https://doi.org/10.6087/kcse.383

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Abstract PDF Supplementary Material: Purpose
This study investigated the factors influencing data paper authors’ continuance intention to publish in data journals, drawing on the post-acceptance model and the unified theory of acceptance and use of technology. Based on these theoretical frameworks, four factors—perceived usefulness, satisfaction, effort expectancy, and social influence—were hypothesized to be associated with authors’ continuance intention.
Methods
A cross-sectional survey was conducted using an online questionnaire distributed to authors who had published in eight data journals where data papers constituted more than 20% of all publications. In total, 453 responses were collected, resulting in a 6.2% response rate. Ordered logistic regression analysis was employed to identify significant influencing factors.
Results
The ordered logistic regression analysis indicated that satisfaction and perceived usefulness were positively associated with authors’ continuance intention, while effort expectancy was negatively associated. Among these, satisfaction with a data journal exerted the strongest influence on continuance intention.
Conclusion
These findings underscore the importance for data journal publishers to actively manage authors’ satisfaction throughout the submission and peer review processes. The identification of perceived usefulness as another significant factor suggests that funders and academic institutions should incentivize authors to publish in data journals. Authors who perceived that publishing in a data journal required excessive time were less likely to intend to publish there again. Training in research data management best practices, provided by academic libraries, may help reduce the time burden associated with data preparation and sharing.

Data sharing attitudes and practices of researchers in Korean government research institutes: a survey-based descriptive study: Jihyun Kim, Hyekyong Hwang, Youngim Jung, Sung-Nam Cho, Tae-Sul Seo; Sci Ed. 2023;10(1):71-77. Published online February 16, 2023; DOI: https://doi.org/10.6087/kcse.299

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Purpose
This study explored to what extent and how researchers in five Korean government research institutes that implement research data management practices share their research data and investigated the challenges they perceive regarding data sharing.
Methods
The study collected survey data from 224 respondents by posting a link to a SurveyMonkey questionnaire on the homepage of each of the five research institutes from June 15 to 29, 2022. Descriptive statistical analyses were conducted.
Results
Among 148 respondents with data sharing experience, the majority had shared some or most of their data. Restricted data sharing within a project was more common than sharing data with outside researchers on request or making data publicly available. Sharing data directly with researchers who asked was the most common method of data sharing, while sharing data via institutional repositories was the second most common method. The most frequently cited factors impeding data sharing included the time and effort required to organize data, concerns about copyright or ownership of data, lack of recognition and reward, and concerns about data containing sensitive information.
Conclusion
Researchers need ongoing training and support on making decisions about access to data, which are nuanced rather than binary. Research institutes’ commitment to developing and maintaining institutional data repositories is also important to facilitate data sharing. To address barriers to data sharing, it is necessary to implement research data management services that help reduce effort and mitigate concerns about legal issues. Possible incentives for researchers who share data should also continue to be explored.

Citations

Citations to this article as recorded by

Six Elements in Promoting Open Science: Malaysian academicians’ research practices in information science
Wahidah Mohd Zain, Paula Lackie, Zahril Shahida Ahmad, Norkamarizal Kamarudin, Siti Khairiyah Nordin
Environment-Behaviour Proceedings Journal.2025; 10(SI31): 57. CrossRef
Factors influencing authors’ intention to continue publishing in data journals: a cross-sectional survey
Seungeun Lee, Jihyun Kim
Science Editing.2025; 12(2): 183. CrossRef
Korean scholarly journal editors’ and publishers’ attitudes towards journal data sharing policies and data papers (2023): a survey-based descriptive study
Hyun Jun Yi, Youngim Jung, Hyekyong Hwang, Sung-Nam Cho
Science Editing.2023; 10(2): 141. CrossRef
Data sharing and data governance in sub-Saharan Africa: Perspectives from researchers and scientists engaged in data-intensive research
Siti M. Kabanda, Nezerith Cengiz, Kanshukan Rajaratnam, Bruce W. Watson, Qunita Brown, Tonya M. Esterhuizen, Keymanthri Moodley
South African Journal of Science.2023;[Epub] CrossRef
Identifying key factors and actions: Initial steps in the Open Science Policy Design and Implementation Process
Hanna Shmagun, Jangsup Shim, Jaesoo Kim, Kwang-Nam Choi, Charles Oppenheim
Journal of Information Science.2023;[Epub] CrossRef

Status and factors associated with the adoption of data sharing policies in Asian journals: Jihyun Kim, Seo Young Bai; Sci Ed. 2022;9(2):97-104. Published online August 19, 2022; DOI: https://doi.org/10.6087/kcse.274

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324 Download
5 Web of Science
5 Crossref

Abstract PDF

Purpose
This study investigated the current status and factors associated with adopting data sharing policies in Asian journals. Data sharing policies vary by country and region, and few studies have examined the trends and factors related to these policies in journals across the Asian region.
Methods
The 2020 Scimago Journal and Country Rank was used to download data about 1,143 Asian journals indexed in Web of Science. Excluding 40 journals inaccessible via the Internet or without English-language websites and author guidelines, 1,103 journals were analyzed through descriptive statistical analyses and the chi-square test.
Results
Of the 1,103 journals, 325 (29.5%) had data sharing policies, showing a moderate level of policy adoption among Asian journals. The results of the chi-square test suggested that the impact factor and publisher type (whether a publisher was commercial) were significantly associated with the presence of data sharing policies in journals, but subject categories were not identified as a significant factor. Regarding the strength of data sharing policies, most journals provided policies that only encouraged data sharing.
Conclusion
Policies only encouraging data sharing are unlikely to lead to actual data sharing; thus, considering varying levels of policy strength and effective ways to induce authors’ compliance with the policies is important. Further research needs to examine other factors affecting the presence or strength of data sharing policies.

Citations

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Open science indicator compliance by Spanish scientific journals
María Ángeles Coslado, Daniela De Filippo, Elías Sanz-Casado
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Analyzing AI use policy in LIS: association with journal metrics and publisher volume
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Scientometrics.2024; 129(12): 7623. CrossRef
Analyzing Data Sharing Policies in Library and Information Science: Journal Metrics, Open Access Status, and Publisher Volume
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Journal metrics, document network, and conceptual and social structures of the Korean Journal of Anesthesiology from 2017 to July 2022: a bibliometric study
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Korean Journal of Anesthesiology.2023; 76(1): 3. CrossRef

Korean researchers’ motivations for publishing in data journals and the usefulness of their data: a qualitative study: Jungyeoun Lee, Jihyun Kim; Sci Ed. 2021;8(2):145-152. Published online August 20, 2021; DOI: https://doi.org/10.6087/kcse.246

7,367 View
207 Download
3 Web of Science
3 Crossref

Abstract PDF

Purpose
This study investigated the usefulness and limitations of data journals by analyzing motivations for submission, review and publication processes according to researchers with experience publishing in data journals.
Methods
Among 79 data journals indexed in Web of Science, we selected four data journals where data papers accounted for more than 20% of the publication volume and whose corresponding authors belonged to South Korean research institutes. A qualitative analysis was conducted of the subjective experiences of seven corresponding authors who agreed to participate in interviews. To analyze interview transcriptions, clusters were created by restructuring the theme nodes using Nvivo 12.
Results
The most important element of data journals to researchers was their usefulness for obtaining credit for research performance. Since the data in repositories linked to data papers are screened using journals’ review processes, the validity, accuracy, reusability, and reliability of data are ensured. In addition, data journals provide a basis for data sharing using repositories and data-centered follow-up research using citations and offer detailed descriptions of data.
Conclusion
Data journals play a leading role in data-centered research. Data papers are recognized as research achievements through citations in the same way as research papers published in conventional journals, but there was also a perception that it is difficult to attain a similar level of academic recognition with data papers as with research papers. However, researchers highly valued the usefulness of data journals, and data journals should thus be developed into new academic communication channels that enhance data sharing and reuse.

Citations

Citations to this article as recorded by

Factors influencing authors’ intention to continue publishing in data journals: a cross-sectional survey
Seungeun Lee, Jihyun Kim
Science Editing.2025; 12(2): 183. CrossRef
Development and validation of the motivation to publish scale-scientific articles (EMP-AC) for Peruvian university students
Oscar Mamani-Benito, Julio Torres-Miranda, Edison Effer Apaza-Tarqui, Madona Tito-Betancur, Wilter C. Morales-García, Josué Edison Turpo-Chaparro
Frontiers in Education.2023;[Epub] CrossRef
Korean scholarly journal editors’ and publishers’ attitudes towards journal data sharing policies and data papers (2023): a survey-based descriptive study
Hyun Jun Yi, Youngim Jung, Hyekyong Hwang, Sung-Nam Cho
Science Editing.2023; 10(2): 141. CrossRef

Data journals: types of peer review, review criteria, and editorial committee members’ positions: Sunkyung Seo, Jihyun Kim; Sci Ed. 2020;7(2):130-135. Published online August 20, 2020; DOI: https://doi.org/10.6087/kcse.207

12,062 View
196 Download
7 Web of Science
6 Crossref

Abstract PDF Supplementary Material

Purpose
This study analyzed the peer review systems, criteria, and editorial committee structures of data journals, aiming to determine the current state of data peer review and to offer suggestions.
Methods
We analyzed peer review systems and criteria for peer review in nine data journals indexed by Web of Science, as well as the positions of the editorial committee members of the journals. Each data journal’s website was initially surveyed, and the editors-in-chief were queried via email about any information not found on the websites. The peer review criteria of the journals were analyzed in terms of data quality, metadata quality, and general quality.
Results
Seven of the nine data journals adopted single-blind and open review peer review methods. The remaining two implemented modified models, such as interactive and community review. In the peer review criteria, there was a shared emphasis on the appropriateness of data production methodology and detailed descriptions. The editorial committees of the journals tended to have subject editors or subject advisory boards, while a few journals included positions with the responsibility of evaluating the technical quality of data.
Conclusion
Creating a community of subject experts and securing various editorial positions for peer review are necessary for data journals to achieve data quality assurance and to promote reuse. New practices will emerge in terms of data peer review models, criteria, and editorial positions, and further research needs to be conducted.

Citations

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What Are Journals and Reviewers Concerned About in Data Papers? Evidence From Journal Guidelines and Review Reports
Xinyu Wang, Lei Xu
Learned Publishing.2025;[Epub] CrossRef
Peer review of data papers: Does it achieve expectations for facilitating data sharing and reuse?
Chenyue Jiao, Peter T. Darch
Journal of Information Science.2025;[Epub] CrossRef
Unleashing the power of AI in science-key considerations for materials data preparation
Yongchao Lu, Hong Wang, Lanting Zhang, Ning Yu, Siqi Shi, Hang Su
Scientific Data.2024;[Epub] CrossRef
Dissemination effect of data papers on scientific datasets
Hong Jiao, Yuhong Qiu, Xiaowei Ma, Bo Yang
Journal of the Association for Information Science and Technology.2024; 75(2): 115. CrossRef
The data paper as a sociolinguistic epistemic object: A content analysis on the rhetorical moves used in data paper abstracts
Kai Li, Chenyue Jiao
Journal of the Association for Information Science and Technology.2022; 73(6): 834. CrossRef
Korean researchers’ motivations for publishing in data journals and the usefulness of their data: a qualitative study
Jungyeoun Lee, Jihyun Kim
Science Editing.2021; 8(2): 145. CrossRef

An analysis of data paper templates and guidelines: types of contextual information described by data journals: Jihyun Kim; Sci Ed. 2020;7(1):16-23. Published online February 20, 2020; DOI: https://doi.org/10.6087/kcse.185

11,314 View
253 Download
13 Web of Science
16 Crossref

Abstract PDF

Purpose
Data papers are a promising genre of scholarly communication, in which research data are described, shared, and published. Rich documentation of data, including adequate contextual information, enhances the potential of data reuse. This study investigated the extent to which the components of data papers specified by journals represented the types of contextual information necessary for data reuse.
Methods
A content analysis of 15 data paper templates/guidelines from 24 data journals indexed by the Web of Science was performed. A coding scheme was developed based on previous studies, consisting of four categories: general data set properties, data production information, repository information, and reuse information.
Results
Only a few types of contextual information were commonly requested by the journals. Except data format information and file names, general data set properties were specified less often than other categories of contextual information. Researchers were frequently asked to provide data production information, such as information on the data collection, data producer, and related project. Repository information focused on data identifiers, while information about repository reputation and curation practices was rarely requested. Reuse information mostly involved advice on the reuse of data and terms of use.
Conclusion
These findings imply that data journals should provide a more standardized set of data paper components to inform reusers of relevant contextual information in a consistent manner. Information about repository reputation and curation could also be provided by data journals to complement the repository information provided by the authors of data papers and to help researchers evaluate the reusability of data.

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What Are Journals and Reviewers Concerned About in Data Papers? Evidence From Journal Guidelines and Review Reports
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Learned Publishing.2025;[Epub] CrossRef
Peer review of data papers: Does it achieve expectations for facilitating data sharing and reuse?
Chenyue Jiao, Peter T. Darch
Journal of Information Science.2025;[Epub] CrossRef
Dissemination effect of data papers on scientific datasets
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Korean scholarly journal editors’ and publishers’ attitudes towards journal data sharing policies and data papers (2023): a survey-based descriptive study
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Science Editing.2023; 10(2): 141. CrossRef
The data paper as a sociolinguistic epistemic object: A content analysis on the rhetorical moves used in data paper abstracts
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Journal of the Association for Information Science and Technology.2022; 73(6): 834. CrossRef
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Review

Overview of disciplinary data sharing practices and promotion of open data in science: Jihyun Kim; Sci Ed. 2019;6(1):3-9. Published online February 20, 2019; DOI: https://doi.org/10.6087/kcse.149

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237 Download
14 Web of Science
13 Crossref

Abstract PDF

The present study specifies the historical development of data sharing practices in three disciplines—oceanography, ecology, and genomics—along with the evolving progress of movements—e-Science, cyberinfrastructure, and open science—that expedite data sharing in more diverse disciplines. The review of these disciplinary data-sharing practices and the movements suggests opportunities and challenges that would serve as a basis for implementing data-sharing practices. The increasing need for large-scale and interdisciplinary research provides momentum for initiating data sharing. In addition, the development of data repositories and standards for metadata and data format facilitates data sharing. However, challenges need to be addressed, in regard to conflicting issues of patenting data, concerns about privacy and confidentiality, and informed consent that adequately enables data sharing. It is also necessary to consider the needs of the various stakeholders involved in data sharing to incentivize them to improve its impact.

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